Spacecraft, including satellites, are exceptionally complex and expensive machines with thousands of telemetry channels, recording a number of aspects from temperature, radiation, power and instrumentation to computational activities. In addition, advances in engineering and technology are leading to the generation of an increasing amount of such telemetry data.

As these data contain valuable information about the operational status of the spacecraft, monitoring of these channels is a constant necessity as a failure to detect and respond to potential hazards could result in the full or partial loss of the spacecraft. Therefore, anomaly detection is a critical tool to alert operations engineers of unexpected behaviour.

Artificial intelligence (AI) techniques are becoming increasingly used to detect such anomalies in time-series data. They are capable of capturing interactions and dependencies inherent in the telemetry channels, providing important insights into complex system behaviours. The state of the art in anomaly detection currently consists of deep learning Transformer models, which also lie at the heart of generative AI tools such as ChatGPT.

On the other hand, digital twins are virtual models designed to accurately reflect a physical object and can be used to run simulations, study performance issues and generate possible improvements, which can generate valuable insights to be applied back to the original physical object. The concept of a ‘digital twin’ was born at NASA in the 1960s as a “living model” of the Apollo mission.

The concept of a ‘digital twin’ was born at NASA in the 1960s as a 'living model' of the Apollo mission

As part of the Anomaly detection for Spacecraft TelemetRy dAta using Artificial Intelligence (ASTRA-AI) project, a multi-disciplinary research team from the University of Malta has developed a Transformer-based anomaly detection method to capture various types of irregular telemetry signals, with a precision of 99 per cent on spacecraft telemetry datasets from NASA (Soil Moisture Active Passive satellite and the Mars Science Laboratory) and the European Space Agency (ESA OPS-SAT satellite).

One of the outcomes of the project would be to demonstrate that such AI models can also run onboard spacecraft with the limited computational resources available.

In addition, the team has successfully developed a digital twin of a typical Earth-orbiting satellite electric power system. This digital twin will then be used for prognostic and diagnostic purposes, for instance to simulate various types of anomalies and eventually evaluate the performance of the AI model in detecting them.

Gianluca Valentino (Department of Communications and Computer Engineering) and Robert Camilleri (Institute of Aerospace Technologies), both from the University of Malta, are the principal investigator and co-investigator respectively of the ASTRA-AI project, which is financed by Xjenza Malta through the FUSION Space Upstream Programme. The research team also includes research support officers  Asma Fejjari and Alexis Delavault.

Photo of the week

The Horsehead Nebula imaged in three red narrowband wavelengths – Sulfur II, Nitrogen II and H alpha – mapped respectively to red, green and blue in order of decreasing wavelength – from Żurrieq, using a five-inch Newtonian telescope. Photo: Josef BorgThe Horsehead Nebula imaged in three red narrowband wavelengths – Sulfur II, Nitrogen II and H alpha – mapped respectively to red, green and blue in order of decreasing wavelength – from Żurrieq, using a five-inch Newtonian telescope. Photo: Josef Borg

Sound Bites

•         Blue Ghost lander successfully achieves soft landing on the lunar surface: Firefly Aerospace’s Blue Ghost became the second private spacecraft – after Intuitive Machines’ Odysseus spacecraft in 2024 – to achieve a soft-landing on the moon on March 2, landing in Mare Crisium. One of the main goals of the lander’s mission is to gather data in preparation for the arrival of astronauts from the Artemis programme in the years to come, with payload experiments expected to run for the duration of one lunar day – approximately 14 Earth days – before sunset over Mare Crisium forces the solar-powered lander to shut down.

For more soundbites, listen to Radio Mocha every Saturday at 7.30pm on Radju Malta and the following Monday at 9pm on Radju Malta 2 https://www.fb.com/RadioMochaMalta/.

DID YOU KNOW?

•         Voyager 1 is the farthest man-made object from Earth. The spacecraft was launched on September 5, 1977, with the aim to study the outer solar system and the sun’s heliosphere. It made several outer solar system flybys, including the gas giants Jupiter and Saturn and Saturn’s largest moon, Titan. It is now approaching one light day away from Earth – meaning that it currently takes signals travelling at light speed from Earth to the spacecraft (or vice-versa) just under 23 hours and four minutes to reach us. At its current rate, Voyager 1 will take a whopping 17,720 years to reach one light year away from Earth!

•         The Venera series spacecraft are, to date, the only to ever successfully land on hostile Venus! Several Soviet Venera landings between 1975 and 1984 captured details of the Venusian surface, with one of the more successful landings pertaining to the Venera 13 mission in 1982. Venera 13 successfully operated on the Venusian surface for an impressive 127 minutes at a scorching temperature of 457ºC and under a crushing atmospheric pressure of approximately 90 times that at sea level on Earth, capturing the first-ever colour image of the surface of Venus.

For more trivia, see: www.um.edu.mt/think.

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